DeepSeek-R1 vs DeepSeek-V3
Wins 4 of 6 areas
Coding · Agents · Reasoning · Long documents
Wins 1 of 6 areas
Facts
DeepSeek-R1 is the stronger all-rounder.DeepSeek-V3 is cheaper and better at facts.
Scores updated · 55 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- ReasoningHard problems that need careful thinking20DeepSeek-R12 of 3 tests · 1 tie
- Long documentsFinding answers in very long texts20DeepSeek-R12 of 2 tests
- CodingWriting and fixing software21DeepSeek-R12 of 4 tests · 1 tie
- AgentsCarrying out multi-step tasks on its own10DeepSeek-R11 of 3 tests · 2 ties
- FactsGetting facts right instead of making them up12DeepSeek-V32 of 3 tests
- Following instructionsDoing exactly what it is asked11Even1 each
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
DeepSeek-V3 costs 81% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where DeepSeek-R1 pulls ahead
- Reasons across sets of long documentsAA-LCR+17points ahead
- Questions about very long textsLongBench v2+9.6points ahead
- Keeps track of context across a multi-turn chatMulti-Challenge+9.3points ahead
Where DeepSeek-V3 pulls ahead
- Hard command-line tasks in a real terminalTerminal-Bench Hard+9.1points ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+4.4points ahead
- Follows unfamiliar, precisely checkable instructionsIFBench+2points ahead
Every test, side by side
All 55 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-R1
- Terminal-Bench HardDeepSeek-V3 by 9.16.115.2+9.1
- SWE-bench VerifiedDeepSeek-R1 by 7.249.242+7.2
- Terminal-Bench 2.1DeepSeek-R1 by 2.219.116.9+2.2
- SciCodetie38.339tie
AgentsDeepSeek-R1
- τ-Bench V3 · BankingDeepSeek-R1 by 1.76.44.7+1.7
- GDPValtie00tie
- Terminal-Bench 4.0tie00tie
ReasoningDeepSeek-R1
- GPQA DiamondDeepSeek-R1 by 5.370.865.5+5.3
- Humanity's Last ExamDeepSeek-R1 by 3.88.54.7+3.8
- CritPttie0.60tie
FactsDeepSeek-V3
- Vectara HHEM hallucination ratelower is betterDeepSeek-V3 by 5.211.36.1+5.2
- AA-Omniscience · AccuracyDeepSeek-R1 by 530.525.4+5
- AA-Omniscience · Non-hallucinationDeepSeek-V3 by 4.49.714.1+4.4
Long documentsDeepSeek-R1
- AA-LCRDeepSeek-R1 by 1757.740.7+17
- LongBench v2DeepSeek-R1 by 9.658.348.7+9.6
Following instructionsEven
- Multi-ChallengeDeepSeek-R1 by 9.340.731.4+9.3
- IFBenchDeepSeek-V3 by 23941+2
Other results38 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- CodeforcesDeepSeek-R1 by 895 rating points20291134+895 rating
- Codeforces (Rating)DeepSeek-R1 by 895 rating points20291134+895 rating
- AIME 2024DeepSeek-R1 by 40.679.839.2+40.6
- Codeforces (Percentile)DeepSeek-R1 by 37.696.358.7+37.6
- τ²-Bench Telecom (AA run)DeepSeek-V3 by 35.711.447.1+35.7
- CNMO 2024DeepSeek-R1 by 35.678.843.2+35.6
- AIME 2025DeepSeek-R1 by 18.77051.3+18.7
- AlpacaEval2.0 (LC-winrate)DeepSeek-R1 by 17.687.670+17.6
- LiveCodeBenchDeepSeek-R1 by 14.363.549.2+14.3
- HMMT Feb. 2025DeepSeek-R1 by 12.541.729.2+12.5
- AIR-Bench 2024DeepSeek-R1 by 12.152.940.8+12.1
- vectara_avg_summary_lengthDeepSeek-R1 by 11.893.581.7+11.8
- FRAMES (Acc.)DeepSeek-R1 by 9.282.573.3+9.2
- AA-OmniscienceDeepSeek-R1 by 8.5-32.2-40.7+8.5
- MMLU-ProDeepSeek-R1 by 8.18475.9+8.1
- MATHDeepSeek-R1 by 7.197.390.2+7.1
- MATH-500 (EM)DeepSeek-R1 by 7.197.390.2+7.1
- Arena-Hard (GPT-4-1106 judge)DeepSeek-R1 by 6.892.385.5+6.8
- C-EvalDeepSeek-R1 by 5.391.886.5+5.3
- ZebraLogicDeepSeek-V3 by 5.378.784+5.3
- SimpleQADeepSeek-R1 by 5.230.124.9+5.2
- vectara_factual_consistencyDeepSeek-V3 by 5.288.793.9+5.2
- MMLU-ProXDeepSeek-R1 by 575.570.5+5
- Chinese SimpleQA (C-SimpleQA)DeepSeek-V3 by 4.363.768+4.3
- MMLU-ReduxDeepSeek-R1 by 3.892.989.1+3.8
- Aider-PolyglotDeepSeek-R1 by 3.753.349.6+3.7
- IFEvalDeepSeek-V3 by 2.883.386.1+2.8
- simple_safety_testsDeepSeek-R1 by 2.79895.3+2.7
- XSTestDeepSeek-V3 by 2.794.497.1+2.7
- MMLUDeepSeek-R1 by 2.390.888.5+2.3
- CLUEWSCDeepSeek-R1 by 1.992.890.9+1.9
- HarmBenchDeepSeek-V3 by 1.847.949.7+1.8
- AA IntelligenceDeepSeek-R1 by 1.711.49.7+1.7
- Artificial Analysis Coding IndexDeepSeek-R1 by 1.624.623+1.6
- DROP (3-shot F1)tie92.291.6tie
- vectara_answer_ratetie9797.5tie
- anthropic_red_teamtie97.297.1tie
- bbqtie96.696.7tie
Questions people ask
Which is better, DeepSeek-R1 or DeepSeek-V3?
DeepSeek-R1 wins four of the six areas where both have results: coding, agents, reasoning and long documents. DeepSeek-V3 wins facts, and costs 81% less. They are level on following instructions.
Which is better for coding?
DeepSeek-R1. It wins 2 of the 4 coding tests both models report; DeepSeek-V3 wins 1, and 1 is a tie.
Which is cheaper?
DeepSeek-R1 costs $2.00 per million input tokens and $4.00 per million output tokens; DeepSeek-V3 costs $0.24 and $0.90. That makes DeepSeek-V3 about 81% cheaper for the same work.
How do you compare the two?
We use the 55 benchmark tests both models have published scores on. The verdict counts the 17 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 38 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.